دورية أكاديمية
Cost-effectiveness of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) testing and isolation strategies in nursing homes.
| العنوان: | Cost-effectiveness of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) testing and isolation strategies in nursing homes. |
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| المؤلفون: | Bartsch SM; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Weatherwax C; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Martinez MF; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Chin KL; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Wasserman MR; Los Angeles Jewish Home, Reseda, California.; California Association of Long Term Care Medicine, Santa Clarita, California., Singh RD; Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, California., Heneghan JL; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Gussin GM; Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, California., Scannell SA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., White C; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Leff B; Center for Transformative Geriatric Research, Division of Geriatric Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland., Huang SS; Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, California., Lee BY; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York.; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York.; New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York. |
| المصدر: | Infection control and hospital epidemiology [Infect Control Hosp Epidemiol] 2024 Jun; Vol. 45 (6), pp. 754-761. Date of Electronic Publication: 2024 Feb 15. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Cambridge University Press Country of Publication: United States NLM ID: 8804099 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1559-6834 (Electronic) Linking ISSN: 0899823X NLM ISO Abbreviation: Infect Control Hosp Epidemiol Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Jan. 2015- : Cambridge : Cambridge University Press Original Publication: [Thorofare, N.J. ] : SLACK Inc., c1988- |
| مواضيع طبية MeSH: | Nursing Homes*/economics , Cost-Benefit Analysis* , COVID-19*/diagnosis , COVID-19*/economics , COVID-19*/prevention & control , SARS-CoV-2* , COVID-19 Testing*/economics , COVID-19 Testing*/methods, Humans ; United States |
| مستخلص: | Objective: Nursing home residents may be particularly vulnerable to coronavirus disease 2019 (COVID-19). Therefore, a question is when and how often nursing homes should test staff for COVID-19 and how this may change as severe acute respiratory coronavirus virus 2 (SARS-CoV-2) evolves. Design: We developed an agent-based model representing a typical nursing home, COVID-19 spread, and its health and economic outcomes to determine the clinical and economic value of various screening and isolation strategies and how it may change under various circumstances. Results: Under winter 2023-2024 SARS-CoV-2 omicron variant conditions, symptom-based antigen testing averted 4.5 COVID-19 cases compared to no testing, saving $191 in direct medical costs. Testing implementation costs far outweighed these savings, resulting in net costs of $990 from the Centers for Medicare & Medicaid Services perspective, $1,545 from the third-party payer perspective, and $57,155 from the societal perspective. Testing did not return sufficient positive health effects to make it cost-effective [$50,000 per quality-adjusted life-year (QALY) threshold], but it exceeded this threshold in ≥59% of simulation trials. Testing remained cost-ineffective when routinely testing staff and varying face mask compliance, vaccine efficacy, and booster coverage. However, all antigen testing strategies became cost-effective (≤$31,906 per QALY) or cost saving (saving ≤$18,372) when the severe outcome risk was ≥3 times higher than that of current omicron variants. Conclusions: SARS-CoV-2 testing costs outweighed benefits under winter 2023-2024 conditions; however, testing became cost-effective with increasingly severe clinical outcomes. Cost-effectiveness can change as the epidemic evolves because it depends on clinical severity and other intervention use. Thus, nursing home administrators and policy makers should monitor and evaluate viral virulence and other interventions over time. |
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| معلومات مُعتمدة: | R01 GM127512 United States GM NIGMS NIH HHS; R01 HS023317 United States HS AHRQ HHS; R01 HS028165 United States HS AHRQ HHS; U54 TR004279 United States TR NCATS NIH HHS |
| SCR Organism: | SARS-CoV-2 variants |
| تواريخ الأحداث: | Date Created: 20240215 Date Completed: 20240517 Latest Revision: 20240603 |
| رمز التحديث: | 20240603 |
| مُعرف محوري في PubMed: | PMC11102288 |
| DOI: | 10.1017/ice.2024.9 |
| PMID: | 38356377 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1559-6834 |
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| DOI: | 10.1017/ice.2024.9 |